AT&T Labs

About: AT&T Labs is a based out in . It is known for research contribution in the topics: Network packet & The Internet. The organization has 1879 authors who have published 5595 publications receiving 483151 citations.

DSD: A schema language for XML

Abstract: XML (eXtensible Markup Language) is a linear syntax for trees, which has gathered a remarkable amount of interest in industry. The acceptance of XML opens new venues for the application of formal methods such as specification of abstract syntax tree sets and tree transformations.A notation for defining a set of XML trees is called a schema language. Such trees correspond to a specific user domain, such as XHTML, the class of XML documents that make sense as HTML.A useful schema notation must: identify most of the syntactic requirements that the documents in the user domain follow; allow efficient parsing; be readable to the user; allow limited tree transformations corresponding to the insertion of defaults; be modular and extensible to support evolving classes of XML documents.In the present paper, we introduce the DSD (Document Structure Description) notation as our bid on how to meet the requirements above.

Accurate and efficient SLA compliance monitoring

Abstract: Service level agreements (SLAs) define performance guarantees made by service providers, e.g, in terms of packet loss, delay, delay variation, and network availability. In this paper, we describe a new active measurement methodology to accurately monitor whether measured network path characteristics are in compliance with performance targets specified in SLAs. Specifically, (1) we describe a new methodology for estimating packet loss rate that significantly improves accuracy over existing approaches; (2) we introduce a new methodology for measuring mean delay along a path that improves accuracy over existing methodologies, and propose a method for obtaining confidence intervals on quantiles of the empirical delay distribution without making any assumption about the true distribution of delay; (3) we introduce a new methodology for measuring delay variation that is more robust than prior techniques; and (4) we extend existing work in network performance tomography to infer lower bounds on the quantiles of a distribution of performance measures along an unmeasured path given measurements from a subset of paths. We unify active measurements for these metrics in a discrete time-based tool called SLAM. The unified probe stream from SLAM consumes lower overall bandwidth than if individual streams are used to measure path properties. We demonstrate the accuracy and convergence properties of SLAM in a controlled laboratory environment using a range of background traffic scenarios and in one- and two-hop settings, and examine its accuracy improvements over existing standard techniques.

Traffic types and growth in backbone networks

Abstract: We review the growth of the different sources of data traffic on backbones, highlight the importance and nature of IP services today, and discuss the implications on content distribution and efficient use of backbone capacity.

Who Should Own Scientific Papers

Abstract: Electronic publication has changed the relationship between publisher and scientist. This Policy Forum argues, because Federally-supported science is a public good, that authors of works based on such support should retain copyright, and issue licenses to their publishers.

Forward Decay: A Practical Time Decay Model for Streaming Systems

Abstract: Temporal data analysis in data warehouses and datastreaming systems often uses time decay to reduce the importance of older tuples, without eliminating their influence, on the results of the analysis. While exponential time decay is commonly used in practice, other decay functions (e.g. polynomial decay) are not, even though they have been identified as useful. We argue that this is because the usual definitions of time decay are "backwards": the decayed weight of a tuple is based on its age, measured backward from the current time. Since this age is constantly changing, such decay is too complex and unwieldy for scalable implementation. In this paper, we propose a new class of "forward" decay functions based on measuring forward from a fixed point in time. We show that this model captures the more practical models already known, such as exponential decay and landmark windows, but also includes a wide class of other types of time decay. We provide efficient algorithms to compute a variety of aggregates and draw samples under forward decay, and show that these are easy to implement scalably. Further, we provide empirical evidence that these can be executed in a production data stream management system with little or no overhead compared to the undecayed computations. Our implementation required no extensions to the query language or the DSMS, demonstrating that forward decay represents a practical model of time decay for systems that deal with time-based data.